Method for Processing an FM Stereo Signal

ABSTRACT

A method for processing an FM stereo signal. The FM stereo signal is digitized and divided into overlapping blocks, which are transformed into the frequency domain. Individual spectral lines of the difference signal are lowered if these have a higher magnitude than the respective spectral lines of the sum signal. The sum and difference signals are then transformed back.

FIELD OF THE INVENTION

The invention relates to a method for processing an analog FM stereosignal subjected to digital signal processing.

BACKGROUND OF THE INVENTION

The pilot-tone system described in ITU-R BS.450 is used to transmitstereo signals from the FM transmitter. This system applies apreemphasis (high frequency boost) to the left (L) and right (R) audiochannels, before using a matrix which generates a sum signal (L+R)/2 anda difference signal (L−R)/2.

The sum signal is transmitted in base band up to 15 kHz. The differencesignal is transmitted in double sideband modulation, with the 38 kHzcarrier suppressed. To enable the receiver to demodulate the differencesignal, a pilot tone is transmitted with a frequency of 19 kHz, whichcorresponds to half the carrier frequency.

The signal mixture of sum-, difference, and pilot-tone signal isreferred to as a multiplex signal (MPX). The MPX signal and additionalsignals, if necessary (such as RDS) modulate an FM transmitter'shigh-frequency carrier signal in its frequency. The high-frequencybroadcasting is done via an antenna.

A superheterodyne FM receiver receives the high-frequency signal via anantenna. The radio-frequency signal (RF signal) of the antenna isamplified, preselected in the frequency, and moved into an intermediatefrequency (IF) range.

An intermediate frequency filter lets through most of the usable signalbandwidth and filters out most adjacent channel interference. Bysubsequent amplitude limiting of the intermediate frequency signal in alimiter, the amplitude fluctuations in the RF- and/or IF-signalreception are suppressed.

Subsequently, a frequency demodulation takes place that delivers the MPXsignal. This is fed into a stereo decoder.

A block diagram of an MPX stereo decoder is shown in FIG. 1.

A mono receiver evaluates only the sum signal (L+R)/2 in the basebandextending up to 15 kHz. In a stereo receiver, a stereo decoder obtainsthe L and R signals from the MPX signal.

In the stereo decoder, a frequency doubling of the pilot tone signaltakes place, and hence a recovery of the carrier frequency 38 kHz of thedifference signal occurs. The stereo decoder demodulates the doublesideband-modulated difference signal and thus recovers the signal(L−R)/2. The sum signal (L+R)/2 is recovered directly from the baseband.By dematrixing, meaning addition or subtraction of these two signals,the decoder recovers the preemphasized L and R signals again. These arethen subjected to a deemphasis that compensates for the transmitter-sidepreemphasis. The original signals L and R are thus available.

Other decoding methods, such as the switching-decoder, differ from theabove-depicted signal processing with regard to demodulation anddematrixing; however, they can be converted in the above model as seenin signal theory.

The receiver behavior according to current technology is as follows.

The FM pilot tone system should first be considered in theory withrespect to noise.

The constant noise density in the RF- or IF-range is converted by theFM-demodulation process into a frequency-proportional voltage-density.

The MPX-spectrum and noise voltage density (Rauschspannungsdichte) areshown in FIG. 2.

It can be seen from FIG. 2 that the difference signal containssignificantly more noise between 23 and 53 kHz than the sum signal,which only reaches up to 15 kHz.

The monaural audio signal-to-noise ratio SNR_(FM), prevailing after theFM demodulation with respect to +/−75 kHz frequency deviation withoutconsideration of a pre/deemphasis, can be approximated by the followingformula:

SNR_(FM)=3β²((β+1)CNR with the radio-frequent carrier-to-noise-ratio

CNR=A ²/(2B _(T) N ₀)

β is the FM modulation indexA is the amplitude of the carrier signalN₀/2 is the two-sided spectral noise power density with white noiseB_(T) is the radio frequency transmission bandwidthIt can be estimated using the Carson formula by way of

B _(T)=2((β+1)W

W is the audio signal bandwidthThe result obtained with the Carson formula is β+1=B_(T)/2 WUsed in the formula for SNR_(FM) results for β>>1 in

SNR_(FM)=3CNR(B _(T)/2W)³

The above-mentioned formulas apply above the so-called FM threshold,below which the signal quality decreases rapidly and impulse-noise canbe expected, which results in clicks or crackling after demodulation.

The FM threshold at a radio frequency transmission bandwidth of 180 kHzis approximately 11 dB CNR. Above this threshold is:

SNR_(FM)=28 dB+CNR with mono reception

SNR_(FM)=5 dB+CNR with stereo reception

10 dB can further be added when considering a preemphasis/deemphasis of50 μs respectively 13 dB at 75 μs.

The FM threshold of approximately 11 dB corresponds to a monoaudio-to-noise ratio of 39 dB+deemphasis-gain. In case of a deemphasisof 50 μs there is likely to be at least a 49 dB mono audiosignal-to-noise ratio, or 26 dB stereo audio signal-to-noise ratio. Withregard to a 40 kHz frequency deviation, an audio signal-to-noise ratioof 43.5 dB mono and 20.5 dB stereo is to be expected. The mono-gain inthe audio signal-to-noise ratio at the FM threshold is 23 dB. In thereceiver, the mono-gain [N(mono)−N(stereo)] decreases with increasingaudio signal-to-noise ratio, as can be seen from the limiter curve of anexemplary FM receiver shown in FIG. 3.

The audio signal-to-noise ratio SNR is limited upwards by the inherentnoise of the rest of the transmission chain. In FIG. 3 the solid curve N(stereo) shows the size of the noise N of an FM stereo reception. Thedashed line N shows the function “stereo blend” which reduces the levelof the difference signal

according to a falling of the antenna input voltage below a threshold(here about 100 μV antenna voltage). The noise power N is kept at areduced level and does not rise further. The result is an increasingdeterioration of the L-R channel separation (stereo blend) up to mono(L=R, i.e., no channel separation).

From approximately 40 μV, the useful signal reaches its full level. Thedistance from the curve N to the curve S+N is the audio signal-to-noiseratio.

According to current technology, a reduction of the level of thedifference signal is used to raise the audio signal-to-noise ratio atthe expense of the L-R channel separation. The reduction can be madebroadband or in frequency ranges, such as in the high frequencies, anddepends on the extent of external signals, external criteria, or anestimate of the interference signal.

Further actions in the receiver to reduce the audibility ofinterferences in the audio frequency range or MPX range are lowering ofthe higher audio frequencies (hi-blend, hi-cut) during strong noise, andvolume-reduction or muting (muting, noise blanker) during stronginterference. These also have an effect on the sum signal (mono signal).

OBJECT OF THE INVENTION

Given this background, it is an object of the invention to improve theaudible stereo audio signal-to-noise ratio without limiting theL-R-channel separation further. The improved signal-to-noise ratioshould be, in particular, the mono-quality.

Furthermore, the invention relates to the steps of improvement from thesignal itself without the help of external signals or external criteria(such as the antenna voltage).

SUMMARY OF THE INVENTION

The object of the invention is already achieved by a method forprocessing an FM stereo signal according to one of the independentclaims.

Preferred embodiments and further refinements of the invention aresubject matter of the dependend claims, the descriptions as well as thedrawings.

The invention relates to a method for processing an analog FM stereosignal. The invention therefore relates to the processing of analogradio signals broadcasted in stereo sound.

The analog stereo signal can be used in the manner described in theintroduction as a sum and difference signal as well as a signal in whichthe left and right channels are separated from each other.

The method according to the invention for processing an FM stereo signalcan also be characterized in that an FM stereo signal is digitized, thedigitized signal is subjected to a signal processing, and is thentransformed back into the analog signal.

According to the invention, the signal processing is performeddigitally, i.e. the processing of the signal is performed by means of amicroprocessor in digital form.

For this purpose, the analog FM stereo signal, as sum and differencesignal, is digitized. This digitized signal is divided into overlappingblocks.

The block length is preferably greater than the time shift between thesum and the difference signal.

In particular, the block length can be between 10 and 1000 ms,preferably between 50 and 150 ms. A large block length leads to a highfrequency resolution, but allows for a rather reduced noise reductionbecause the useful signal spectrum approximates the interference signalspectrum.

The overlapping blocks allow a consecutive transformation into thefrequency domain, and there, a signal processing. After conversion, thesignal is available as a difference and sum channel spectrum, in whichthe signal, blockwise, is divided into a plurality of spectral linesrepresenting the magnitude and the phase of the signal at the respectivefrequency.

Thus, a first aspect of the invention relates to a digital signalprocessing, in which the analog

signal is digitized and at least partially processed in the frequencydomain. For this purpose, thespectral lines of the differential signal spectrum are compared with thecorresponding spectral lines of the sum signal spectrum. It isunderstood that under “signal spectrum” in each case the signalmagnitude spectrum is understood, and thus the comparison refers to therespective amounts. Forfurther explanations, these are considered to be logarithmic.

According to the invention spectral lines of the difference signal,spectrum are attenuated if they have

a higher amount than the respective spectral lines of the sum signalspectrum.

Preferably, the lowering is made to the amount of the sum signalspectrum. However, it can remain a difference to the amount of the sumsignal spectrum, in particular a difference of a maximum of +/−6 dB,preferably +/−3 dB.

This aspect of the invention is based on the assumption that the stereosignal comprises only signal components that can be localized within thestereobase.

It follows that a spectral line of the difference signal spectrum cannothave a higher magnitude than the corresponding spectral line of the sumsignal spectrum. The conclusion applies to intensity stereophony(simultaneous sum and difference signal). It applies to time-basedstereophony if the time difference between the two signals or theirportions do not lead to altered magnitude spectra. The latter is true ifthe block length clearly exceeds the time difference.

By transforming into the frequency domain, a processing of the signalcomponents in digitized form is possible in a simple way. In particular,this can be done purely via software, for example, on a smartphone orconsumer electronics device. Preferably, the entire signal processing isdone purely via software, also including the processing in the timedomain.

After this digital signal processing, the sum and difference signal istransformed back and the overlapping blocks are added.

The signal can now be dematrixed and converted into an analog signal forthe drive of a loudspeaker.

According to the further rules, that are also described in concreteterms, in particular, interference-induced drops of the sum signal aswell as interference-related increases of the spectra can be recognizedand exceptions can be defined not to falsify the (undisturbed) signaland to reduce interference if necessary.

In a further embodiment of the invention, the frequency correspondingspectral lines of the

difference signal spectrum are not attenuated at all or are lessattenuated, if the width of a relative minimum of the sum signalspectrum is below a threshold and the depth is above a threshold, thuscreating a cancellation.

This approach to the reduction of the difference signal is based on theconsideration of time differences of the signals, which lead tointerferences.

Interference leads to level drops (cancellations) and/or level increasesat specific points of the

frequency spectrum.

However, such drops have a narrow bandwidth. If the interference-relateddrops were used to cause an attenuation of the difference signal atthese points, the FM stereo signal would be distorted.

In a further embodiment of the invention, in the range of a localmaximum of the difference signal spectrum, the latter is compared withthe sum signal spectrum, and the difference signal spectrum is notattenuated in this range or is less attenuated, if a maximum of the sumsignal spectrum lies within the frequency bandwidth of the maximum ofthe difference signal spectrum.

This further embodiment of the invention relates to the treatment oflocal maxima, which can, as well as local minima, be caused by timedelay phenomena.

The further embodiment of the invention according to claims 2 and 3therefore provides an exception to the rule defined in claim 1.

Cancellations and local maxima of a frequency spectrum can be identifiedas such by their frequency bandwidth and their distance to the spectralsubstitute value.

A median filtering of the spectrum produces a reference curve. If thedistance of the spectrum to the reference curve exceeds a thresholdvalue, a cancellation or a local maximum is identified. Their frequencybandwidth corresponds to the number of consecutive spectral lines whichexceed the threshold value.

The median value is calculated from the spectral values of the spectrumwithin a window around a frequency. It serves here as a substitute valuein the spectrum and bridges outliers of the spectrum level.

For cancellations, local maxima of the sum spectrum and local maxima ofthe difference signal spectrum, distinct threshold values are providedin dB, which a distance must exceed in order to confirm anidentification.

If, therefore, such a cancellation is confirmed, the lowering of thecorresponding spectral lines of the difference signal spectrum is notmade according to the previously defined rule. That is, an exception ismade to the previously defined rule.

A further embodiment of the invention provides that time differencesbetween the sum and difference signals are determined via a similarityanalysis or a correlation of the signals in the time domain.

Specifically, by cross-correlation and/or consideration of thecancellation in the frequency domain, in particular by comparing therespective frequencies and the respective bandwidths of thecancellations in the sum and difference signal spectra, the presence oftime-based stereophonic portions in the signals can be determined. Thisis true if cancellations occur in the sum and difference signals atdifferent frequencies.

In a further embodiment of the invention, in a block-wise similarityanalysis, the analysis result of the previous block is taken over if thecurrently processed block shows a signal-to-noise ratio (SNR) lyingbelow a threshold value. For example, if the signal-to-noise ratio fallsbelow a threshold value in a block, the IS/LS analysis becomesunreliable. Therefore, according to this embodiment, the decision of thelast block with a high signal-to-noise ratio is adopted.

If the calculation yields the presence of time-based stereo signalportions, again according to this embodiment of the invention, the ruledefined in claim 2 and/or 3 takes effect. This ensures that the exeptionrule according to claim 2 and/or 3 is only used with time-basedstereophony.

The further developments of the invention, as defined in claims 2 to 4,serve to avoid sound distortions, in particular to prevent a fault-freesignal from being corrupted in an audible manner.

In a further embodiment of the invention, in the case of a cancellationof a spectral line in the sum signal spectrum, the spectral line of thedifference signal is only reduced to a spectral substitute value, inparticular to a median value of the sum signal spectrum.

This is a differentiation of the cancellation rule.

If the magnitude of the difference signal spectrum at a frequency isgreater than the corresponding value of the sum signal spectrum, thedifference signal spectrum is lowered in case of a cancellation to themedian of the sum signal spectrum determined for this frequency.

The reduction to the spectral substitute value of the sum signalspectrum reduces interference-induced increases in the difference signalspectrum and avoids a sound distortion by an otherwise greater reductionof the spectral line.

In a further embodiment of the invention, the difference signal in thetime domain is limited to the envelope curve of the sum signal whosemaxima are held (peak hold) for a period of time before and after theentry time of the maximum. The so-changed envelope curve or the sumsignal is multiplied by a factor of greater than 1, in particular afactor between 1 and 2.

This aspect of the invention is based on the assumption that the stereosignal does not map spots outside the stereo base. It follows that thedifference signal cannot have a higher magnitude than the sum signalmultiplied by a factor which takes into account a statistical signalincrease which can occur with certain signal constellations of the sumand difference signals.

Preferably, the restriction of the difference signal in the time domainto the envelope curve of the sum signal is only performed when atransient character of the signal is detected via an evaluation of thesignal or the envelope curve of the sum signal.

This is preferably done before the attenuation of individual spectrallines of the difference signal, that is to say, before processing in thefrequency domain.

The envelope curve can be multiplied by a factor, in particular anempirical factor between 1.1 and 2.0, preferably between 1.3 and 1.6.

The invention further relates to a computer program which includes aplurality of instructions which can be stored on a computer, inparticular on a smartphone or consumer electronic device. Theinstructions, when processed by a microprocessor or microcontroller,perform a method as described above.

The invention relates in particular to a purely software-basedprocessing of an analog FM stereo signal in a device such as, forexample, a smartphone, but also in a radio with digital signalprocessing, in particular a car radio.

It is clear that, in the case of known devices in which digital signalprocessing is already present, all necessary further process steps, ifappropriate, can be integrated into this digital processing.

In particular, in the case of smartphones and consumer electronicsdevices which comprise a microprocessor, the hardware componentsrequired for carrying out the method according to the invention arepresent when the device is provided with a tuner for receiving analog FMstereo signals.

The method according to the invention can be implemented, in particular,purely through software, via a program (app). The instructions forcarrying out the method according to the invention are stored on a datastore.

In a further embodiment of the invention, the signal processing takesplace in an application-specific integrated circuit (ASIC), whichcarries out the signal processing according to the method according tothe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a block diagram of a MPX stereo decoder.

FIG. 2 shows a MPX-spectrum and noise voltage density.

FIG. 3 shows a limiter curve of an exemplary FM receiver in which themono-gain [N(mono)−N(stereo)] decreases with increasing audiosignal-to-noise ratio.

FIG. 4 shows a diagram of a signal division into the channels L and R inthe case of pure IS.

FIG. 5 shows the sum and difference signals as well as the resultingenvelope curve of the sum signal.

FIG. 6 shows the sum signal and the difference signal, with thedifference signal being partly outside the envelope curve, and areduction of the disturbance in the time domain being possible.

FIG. 7 shows a reduction of the disturbance in the time domain is notpossible.

FIG. 8 shows that, in the frequency domain, a reduction of thedisturbance is possible.

FIG. 9 shows a critical band No. 9 from 920 Hz to 1080 Hz with 30spectral lines, three of which are not lowered.

FIG. 10 shows the masking curves of a 1 kHz sinusoidal for differentlevels.

FIGS. 11a and 11b show an example in which L=sine signal 900 Hz andR=sine signal 300 Hz.

FIG. 12 shows the sum signal and the difference signal associated withFIGS. 11a and 11 b.

FIG. 13 shows an example of an AB microphone installation.

FIG. 14 shows the difference signal spectrum and cancellations in thesum signal spectrum at LS.

FIG. 15 shows the disturbed difference signal spectrum, which can bereduced to the median value of the sum signal spectrum.

FIG. 16 shows a frequency-selective noise spectrum of the differencesignal.

FIG. 17a shows the median-filtered difference signal spectrum and localmaxima of the difference signal spectrum.

FIG. 17b shows the sum signal spectrum and the difference signalspectrum as well as local maxima of both spectra.

FIGS. 18a and 18b show typical delta KOV at LS (18 a) and IS (18 b).

FIG. 19 shows the masking in the time domain (“temporal masking”).

FIG. 20 shows the time course of an undisturbed guiro without signalprocessing.

FIG. 21 shows the time course of a noisy guiro after signal processingin the frequency domain.

FIG. 22 shows the time course of the noisy guiro after signal processingin the time and frequency domain.

FIG. 23a shows the overall view of the signal processing, predominantlyin the time domain, as a block diagram.

FIG. 23b shows the overall view of the signal processing, predominantlyin the frequency domain, as a block diagram.

FIG. 24 shows an embodiment of the identification of cancellations inthe sum signal spectrum shown as a block in FIG. 23 b.

FIG. 25 shows the identification and the comparison of the maximadepicted in FIG. 23 b.

DETAILED DESCRIPTION

The method according to the invention will be explained in detail belowwith reference to an exemplary embodiment and with reference to thefurther drawings.

1. Overview of the Method

In which form (time domain or frequency domain) and to which extent thedifference signal may differ from the sum signal without restricting thestereo base, is theoretically derived in the following manner. Theresulting rules for signal processing allow the disturbed differencesignal to be approached audibly to the undisturbed difference signalwithout explicit knowledge of the interfering signal or without externalinformation. The interfering signal does not need to be estimated.

The rules are obtained exclusively from the signals L and R or (L+R),and (L−R). Therefore, it is also possible to process recorded stereosignals of an FM stereo receiver after the fact.

The signal processing of the difference signal according to the derivedrules will result in an approximation of the undisturbed differencesignal.

Thereby the achieved noise reduction is not dependent on a signalthreshold. It works in all signal level ranges.

The method yields the effect of individual frequency portions within thecritical bandwidth to the hearing as well as the masking effect.

The modular structure of this method allows for different quality levelsdependent on the varying realization efforts of signal processing to beimplemented.

The method according to the invention for the signal processing of an FMstereo signal processes audio signals of the left and right channelafter a stereo decoding in the receiver in digitized form. The sumsignal and difference signal can alternatively be processed.

It is assumed that functions such as stereo blend and hi-blend areturned off, and the muting level and the volume reduction in the case ofsevere disturbances is adapted to the method, to fully exploit thebenefits of the method.

The method adapts the signal processing to the signal characteristics.

To this end, various signal analyses are carried out. The aim will befor the undisturbed signals to remain practically audibly unchanged,while the disturbed signals will be freed very effectively ofinterference while preserving the L-R channel separation.

2. Block Structure and Overlap-Add

Signal processing takes place in blocks, which means the audio data ofboth channels is collected for a period of time and then processed.Signal processing is non-linear and takes place in the time andfrequency domain. In the following, the term “frequency domain” standsfor the domain of the transformed signal. The transformation may be aFourier transform or a wavelet transformation or the like.

The signal processing steps for noise reduction are embedded in aweighted-overlap-add structure (WOLA). It's possible to perform aconsecutive transformation into the frequency domain by WOLA. The WOLAstructure used consists of the following parts:

-   -   Creation of an overlapping block structure.    -   Multiplication of the block with an analysis window function        (here, root-Hanning). This facilitates the use of a        transformation into the frequency domain without so-called        spectral leakage.    -   Zero-padding the block with sample values to the desired block        length for the transformation into the frequency domain.    -   Transformation into the frequency domain, non-linear processing,        back-transformation into the time domain    -   Multiplying the block with a synthesis-window function (here,        root-Hanning) to reduce artifacts caused by the non-linear        processing. The synthesis-window function hides this error at        block boundaries and avoids audible discontinuities.    -   Addition of overlapping blocks (overlap-add)

The WOLA is signal-transparent within itself, i.e., as long as nochanges to the signal are made, the output signal corresponds to theinput signal. The synthesis-window function and the block overlap reduceunwanted signal changes, especially at block boundaries.

A detailed description can be found under point 9: Signal Processing.

3. Intensity Stereophony (IS)

In the case of pure intensity stereophony, a musical instrument or avoice within the stereo base is mapped to a virtual spot by splittingthe signal at a certain ratio to the left (L) and right (R) channel. Theplace is defined by the relative levels of the left channel (L) andright channel (R). The signals in L and R are equal to each other intime/phase.

During reproduction, human hearing can determine the auditory eventdirection, and thus the origin of the sound source within the stereobase, by means of level differences between the left and right ear.

FIG. 4 shows the diagram of a signal division into the channels L and Rin the case of pure IS.

The stereo base extends from the far left (R=0) to the center (L=R) upto the far right (L=0).

For FM stereo broadcasting, the audio signals L(t) and R(t) arematrixed.

A sum-signal σ(t) and a difference signal δ(t) is created. For L, R, σand δ for the sake of simplicity, the time dependence is henceforthassumed and is omitted in the remaining representation.

The matrixing specification is as follows:

σ=(L+R)/2 and 5=(L−R)/2

A de-matrixing takes place on the receiving side:

L=σ+δ and R=σ−δ

First a single sine wave signal should be considered.

If we assume that on the transmitting end there is no excess width ofthe stereo base, in other words R=0 and L=0 represent the extremelocations of the stereo base, then results for

R=0: δ=σ

and for L=0: δ=−σ

deriving: |δ|=|σ|

For each spot mapped within the stereo base, regarding the sine wavesignal follows

|δ|≦|σ|  Rule 1

where the equality holds true for the cases R=0 and L=0.

The absolute value function |σ| can be regarded as an envelope, which issupported by relative maxima/minima of the sum signal.

FIG. 5 shows exemplary sum and difference signals as well as theresulting envelope curve (of a complex signal and not of a simplesinusoidal signal).

-   -   Rule 1 can be defined in the time and in the frequency domain of        the audio signals:    -   a. Time domain: At any given time, the absolute value of the        difference signal is smaller than that of the sum signal, or is        at most equal to it. The difference signal lies within the        envelope of the sum signal.    -   b. Frequency domain: At each frequency, the power of the        difference signal is smaller than the power of the sum signal,        or is at most equal to it.

Rule 1 leads to the following signal processing according to theinvention:

If the difference signal is superimposed with noise and theabove-mentioned rule is violated in the time domain or frequency domain,then the difference signal can be reduced in its absolute value to thatof the sum signal at the appropriate time resp. at the correspondingfrequency.

The frequency spectrum with infinitesimal resolution is defined as thesum of spectral lines. Each spectral line can be interpreted as a vectorwith an amplitude value (magnitude) and an associated phase value. Adisturbance can increase or decrease the amplitude value, change thephase value, and leads to a corrupted channel separation via thedematrixing.

The amplitude value is then reduced according to Rule 1b to the value ofthe sum signal spectrum (corresponds to the case R=0 and L=0,respectively). Because of the infinitesimally small bandwidth, it isirrelevant whether the power originates from the useful or interferencesignal or both. The phase value is processed unchanged.

The signal processing is to be illustrated in three examples accordingto FIG. 6 through FIG. 8:

As shown in FIG. 6, the sum signal is superimposed by the differencesignal such that the sum signal cannot be seen in the manner shown insections. The difference signal is partly outside the envelope curve. Acut-off of the interference signal components, and thus a reduction ofthe disturbance in the time domain, is therefore possible.

According to the illustration in FIG. 7, however, a reduction of thedisturbance in the time domain is not possible. Since the disturbeddifference signal is still within the envelope curve of the sum signal,no level reduction can occur in the time domain.

In the frequency domain, a reduction of the disturbance is possible, asshown in FIG. 8. The power of a frequency f in the disturbed differencesignal can be reduced to the power of the corresponding frequency in thesum signal. The extent of the reduction is indicated here as delta.

The application of rule 1 in the frequency domain represents the largestshare of noise reduction.

Often, many spectral lines of the difference signal are lower than thoseof the sum signal, e.g., in the case of an undisturbed signal in whichthe stereo effect is not extremely pronounced (e.g., R=L/2).

A reduction of amplitude values of the difference signal spectrum isonly carried out if the disturbance raises the amplitude value above thevalue of the sum signal spectrum. This can occur particularly in thecase of quiet passages, in which the disturbance dominates the usefulsignal.

With increasing frequency resolution (corresponding to increasing blocklength), more details of the spectra are opened, also in the form ofgaps and sinks of the sum signal spectrum. The method exploits thissituation and, in particular, lowers interfering signals in thedifference signal spectrum at these points.

It is relevant to human hearing how well this interference suppressionworks within the frequency groups. In a frequency group or criticalbandwidth, the human hearing evaluates the frequencies or spectral linesin common. There are 24 frequency groups from 0 to 20000 Hz.

FIG. 9 shows the critical band No. 9 from 920 Hz to 1080 Hz with 30spectral lines, three of which are not lowered.

The above mentioned noise reduction at high frequency resolution causesan increase in the SNR within the frequency groups formed in thehearing.

The sum signal spectrum and the interference-reduced difference signalspectrum are mapped by the dematrixing into the channels L and R. In thefrequency range there is a masking of possible residual errors of theinterference suppression process. The masking depends on the statisticalproperties and the spectral distribution of the useful signals in theleft and right channels.

FIG. 10 shows the masking curves of a 1 kHz sinusoidal for differentlevels. If the 1 kHz tone has a level of 100 dB, for example, a 2 kHztone with 70 dB cannot be perceived in the same channel.

It is understood that such masking effects in the frequency range alsoplay a role for the perception of the processed signal, in particularwith regard to residual errors, even if these masking effects do notenter the processing of the signal.

The frequency groups are arranged in an approximately logarithmicfrequency scale. For the purposes of the invention, for example alogarithmic scaling is also conceivable in the transformation into thefrequency domain. In the exemplary embodiment shown here, however, alinear scaling is performed.

According to the method of the invention, preferably no spectral linesof the audio signal are combined into frequency groups. Rather, theevaluation of frequency groups is left to the human hearing, whereby theabove-mentioned masking effects enter the perception of human hearing.

If we consider a composite signal instead of a single signal

then the situation is somewhat different.

FIGS. 11a and 11b show an example:

L=sine signal 900 Hz, R=sine signal 300 Hz

FIG. 12 shows the sum signal and the difference signal (dotted)

Based on this example it can be seen that the difference signal can havea higher amplitude than the sum signal. Most cases are detected in morecomplex signal constellations with a factor of 1.4. It is also apparentthat the maximum of the sum and difference signal does not necessarilyhave to be concurrent. The envelope curve of the sum signal must beexpanded by the factor k_(IS), and relative maxima/minima of the sumsignal must be held for a certain time so that the maxima/minima of thedifference signal can be included. Since a maximum can occur first ineach of the two signals, the hold time should also apply to periodsprior to the observation time.

The time difference between the extreme values of the sum signal anddifference signal corresponds to a half period of the higher frequencysignal if the frequency ratio is 3:1. A time difference of +/−3 mscorresponds to 83/166 Hz. Frequencies in this range are usually mono,i.e., their share in the difference signal is low. A range of +/−3 mscovers nearly all such effects.

In intensity stereophonic signal constellations, for all mapped spotswithin the stereo base, the below rule applies:

|δ|≦k _(IS)|σ| within a time window of τ_(IS)  modified Rule 1:

with k_(IS)=amplitude factor in composite signals, for example, 1.4with k_(IS)=amplitude factor in single tones, for example, 1.1*with τ_(IS)=peak hold time, e.g., +/−3 ms

The modified rule 1 is in the time domain and in the frequency domain asfollows:

-   -   a. Time domain: The difference signal is within an envelope. The        envelope is based on the relative maxima/minima of the sum        signal, multiplied by a factor of k_(IS). Each newly detected        and with k_(IS) multiplied extreme value is kept within a time        window of τ_(IS) (peak hold).    -   b. Frequency domain: At each frequency, the power of the        difference signal is smaller than the power of the sum signal,        or is at most equal to it.    -   This value (here, for example, 1.1) includes a level of        imbalance of the receiver of 1 dB between the left and right        channel. With of a factor k=1.0 and a level difference between        the left and right audio output, the difference signal would        otherwise be cut unnecessarily.

This results in the following signal processing:

Time Domain:

For each block, the disturbed difference signal is reduced to theenvelope of the sum signal, wherein the envelope takes into accountsignal shifts and amplitude increases. To compute the envelope, therelative maxima/minima (momentary peak values) of the absolute value ofthe sum signal are held (peak hold), and the resulting signal isincreased by the factor k_(IS) (e.g., 1.4) for the range of the timeoffset τ_(IS) (e.g. −3/+3 ms).

It is necessary that the block length (in this case about 100 ms) coversthe time difference between the extreme values of the sum and differencesignals.

Frequency Domain:

The amplitude value of each spectral line of the disturbed differencesignal is reduced to the value of the sum signal. The phase spectrum ofthe difference signal is unchanged and processed further.

4. Time Based Stereophony and Intensity Stereophony with Time BasedStereophonic Fractions (LS)

With pure time based stereophony, a sound source is recorded withdisplaced microphones. The sound travels different distances to themicrophones, depending on the input direction. Within the microphonesignals L and R, signals are formed that have a direction-dependent timedelay. During reproduction, the human ear can determine the direction ofthe auditory event, and thereby locates the sound by the time differencebetween the left and right ear signals.

FIG. 13 shows an example of such an AB microphone installation.

For the path length difference, Δl=a*sin Θ applies for the timedifference, Δt=Δl/c applies, with c=343 m/s, and the microphone distancea.

In practice, there is often no pure time-based stereophony, but anintensity stereophony with time-based stereophonic fractions, alsoreferred to as equivalence stereophony. This manifests itself indifferent phase values in the spectra of the sum and difference signals,but also in non-simultaneous amplitude peaks in the time domain of bothsignals.

Recordings with time based stereophonic fractions are made for examplein AB technology. The so-called Decca Tree is also used to reproducecomplex sound bodies such as an orchestra, for example. Here,additional, laterally arranged supporting microphones are sometimesused. The sound from a source arrives at different microphones.Depending on the sound input direction and the arrangement of themicrophones, individual levels and delay times are obtained for eachmicrophone. The individual microphone signals are processed according tocertain aspects, to a left and a right audio signal.

Depending on the sound input direction and the arrangement of themicrophones, the following effects can be observed after matrixing:

-   -   An auditory event, which is reflected in the difference signal,        is not completely equal to the sum signal, depending on the        input direction of the sound wave.    -   The individual microphone signals are superimposed with their        different time delays, and generate a statistical deviation of        the amplitude of the difference signal compared with the sum        signal. This is especially true for frequencies above the bass        range, in which the individual time delay results in        ambiguousness of the phase (1 m=3 ms=360 degrees at 332 Hz!).

However, when recording, attention is paid to mono-compatibility. Thatmeans, time delay differences are avoided between the microphone signalsto prevent audible cancellation effects in the sum signal. Therefore,the intensity stereophonic portion in the signal predominates and thestatistical amplitude distortion of the difference signal is limited.

This leads to rule 2 of the method according to the invention:

|δ|≦k _(LS)|σ| within the time window of τ_(LS)  Rule 2:

with k_(LS)=amplitude factor, e.g., 1.4with τ_(LS)=peak hold time, e.g., +/−3 ms

Rule 2 is represented in the time and frequency domain as follows:

-   -   a. Time domain: The difference signal is within an envelope. The        envelope is based on the relative maxima/minima of the sum        signal, multiplied by a factor of k_(LS). Each newly detected        and with k_(LS)−multiplied extreme value is kept within a time        window of τ_(LS) (peak hold).    -   b. Frequency domain: At each frequency, the power of the        difference signal is smaller than the power of the sum signal,        or is at most equal to it.

Rule 2 leads to the following processing of signals with time-basedstereophonic fractions:

Frequency domain: Since time-shifted signals have the same magnitudespectra, the amplitude value (magnitude) of the disturbed spectral lineof the difference signal can also be reduced in LS to the correspondingvalue of the sum signal spectrum. However, it is necessary that theblock length (here, approximately 100 ms) covers the major time delaydifferences, i.e., that time-shifted signal components occur in the sameblock.

The phase spectrum is processed further, unchanged.

Time domain: For each block the disturbed difference signal is reducedto the envelope of the sum signal, wherein the envelope takes intoaccount signal shifts and amplitude increases (especially withtransients). To compute the envelope, relative maxima (momentary peakvalues) of the absolute value of the sum signal are held (peak hold),and the resulting signal is increased by the factor k_(LS) (e.g., 1.4)for the time shift range τ_(LS) (e.g. −3/+3 ms).

Rules 1 and 2 can also be applied to frequency groups in the frequencydomain. Thereby the powers of the individual spectral lines areconsidered summarized.

Rule 1 is the consideration for intensity stereophony. Rule 1b or Rule2b is always applied for the implementation of the procedure.

5. Special Signal Constellations in LS

The method according to the invention also involves typical signalconstellations during signal processing in the case of the time basedstereophony:

-   -   Cancellations

When recording signals with time-based stereophonic fractions,frequency-selective cancellations (AL) can occur in the sum and thedifference signal spectrum. Due to different signal path delays of thedisplaced microphones L and R, a cancellation happens, e.g., in the sumsignal σ=(L+R)/2 if a frequency at microphone R undergoes a phaserotation of 180 degrees with respect to microphone L. In the differencesignal δ=(L−R)/2, a cancellation happens if a frequency of themicrophone R undergoes a delay-dependent phase rotation of 0 degrees. Acancellation or destructive interference of sound waves in both signalsat the same frequency can only occur if this frequency is derived from avariety of sound origins or input directions and both arrive at themicrophones with equal amplitude. This is statistically unlikely.Usually, cancellations occur in both signals at different frequencies.

FIG. 14 shows an undisturbed difference signal spectrum at LS.Frequency-selective cancellations in the sum signal spectrum at 2.09 kHzand 2.83 kHz can be seen. Cancellations occur in both spectra atdifferent frequencies.

A cancellation in the sum signal would decrease the difference signalspectrum severely at this frequency, in accordance with rule 2b, and mayimpair the sound of the undisturbed audio signal. If a narrowcancellation is identified, a gain reduction can be avoided.

However, in the case of cancellations in the sum signal spectrum, theunchanged value of the difference signal spectrum is not taken over,since this could be a pure interference signal of any magnitude.Instead, the value of the difference signal is reduced to the medianvalue of the sum signal spectrum as shown in FIG. 15, showing adisturbed difference signal spectrum. Thus, the noise reduction remainsin effect without distorting the useful signal.

-   -   Local level maxima

A local/frequency-selective maximum (LM) in the difference signalspectrum can arise during the recording of time-based stereophonicfractions by constructive interference of sound waves, whereas the sumsignal does not reach this maximum. In this case, it would come to anundesirable level attenuation in accordance with rule 2b.

To avoid a level reduction, there is a check to see if thefrequency-selective level maximum is associated with a higherfrequency-selective SNR. If so, the level remains unchanged and is notlowered. Thereby it is assumed that the noise has a white spectrum inthe extended surrounding of the level maximum and thefrequency-selective level maximum projects beyond this.

However, this strategy fails in the case of noise with afrequency-selective spectrum. Therefore, the sum signal spectrum istaken into account as an additional criterion. Both the sum signalspectrum as well as the difference signal spectrum must extend withtheir frequency-selective maxima levels out of the spectral environmentof the difference signal spectrum. Then you can assume that thefrequency-selective level increase is resulting from the useful and notfrom the interfering signal.

As can be seen in FIG.

14, the sum signal spectrum and the difference signal spectrum disturbedby noise have each two maxima at 2.12 kHz and 2.17 kHz, which rise abovethe values of the closer environment (approximately 59 dB). It cantherefore be assumed that both maxima result from the useful signal, andthat the local SNR is high. These maxima of the difference signalspectrum may remain unchanged for further signal processing.

FIG. 16 shows a frequency-selective noise spectrum. However, thedifference signal spectrum shows several spectral lines with a higherlevel that is not supported by the spectral lines of the sum signal. Itcan be deduced, therefore, that the high-level spectral lines of thedifference signal originate from an interference signal. A reduction tothe level of the sum signal spectrum can be carried out.

Local maxima are identified separately for the sum signal and thedifference signal spectrum. The median-filtered difference signalspectrum can be seen in FIG. 17a . A maximum in one of the spectraexists when the spectrum exceeds its median value for a specified valuein dB.

In FIGS. 17a and 17b , LMSumme and LMDifferenz (labels in the bottom ofthe screen) indicate the maxima of the sum signal spectrum or differencesignal spectrum. If LMSumme lies within the bandwidth of LMDifferenz, asuperordinate local maximum LM is reported, which causes a levelreduction of the difference signal spectrum in the correspondingfrequency bandwidth to be blocked. In the case of the example in FIG.17b , this is true only for a narrow frequency band at 5.75 kHz.

Both cancellations (AL) and local maxima (LM) are identified by means ofmedian filtering. Both cases are incorporated into the spectralcorrection function as non-linear signal processing. LM and ALcontribute to the restoration of the undisturbed difference signalspectrum.

6. Identification of IS and LS

The identification of LS takes place via a cross-correlation (similarityanalysis) of the sum and difference signals. The basic idea behind thisis that the time difference of both signals is determined by thecross-correlation. If this is equal to zero, IS is present; otherwise,LS is present.

Complementarily or alternatively, an identification can take place inthe frequency domain if cancellations occur in the sum and differencesignals at different frequencies.

The cross-correlation function (KKF) is calculated from one block eachof the sum signal and difference signal. In almost all recordings,including those with time-based stereophonic character, the low tonesare monaural. They produce small phase differences at the differentmicrophones, and generally dominate higher frequencies in the level.Time delays at higher frequencies are covered and not recognized by theKKF. In order to avoid this, the sum and difference signals areinitially differentiated in time and only then is the KKF calculated.The differentiation in the time domain corresponds to an increase in thelevel to higher frequencies in the frequency domain.

The KKF is calculated independently of the level by determining thecovariance function (KOV) (for formulas see appendix). Maxima can beidentified by subsequent calculation of the absolute value independentlyof the signal polarity. Maxima are shown at such time shifts, in whichthe differentiated sum and difference signals show similarities. In thecase of pure IS, the maximum shows up at the time shift zero. More KOVmaxima may occur when both signals have inner similarities: thedifference signal is often an attenuated copy of the sum signal. To hidethese maxima, the autocovariance (AKOV) of the sum signal is calculatedand subtracted from the scaled to 1 KOV covariance. If the difference(delta KOV) exceeds a certain threshold value, LS is present; otherwise,IS is present.

FIGS. 18a and 18b show typical delta KOV at LS (18 a) and IS (18 b).

In the case of superimposed disturbances, the above-mentioned methoddoes not provide reliable detection of time-based stereophonic delaysbetween sum and difference signals in each block. Disturbances changethe time course of the difference signal, lead to dissimilarity of sumand difference signals, and consequently reduce the level of delta.Thus, in order to avoid the occurrence of disturbance-related IS/LSfault decisions, the signal-to-noise ratio (SNR) is considered block byblock. The SNR is here defined as the ratio of the power of the sumsignal and difference signal. Should the SNR decrease below a thresholdvalue in a block (making the IS/LS-decision unreliable), the decision ofthe last block with a high SNR is used. The starting value LS ispredetermined.

7. Signal Classification and Temporal Processing

Audio signals can have a transient or stationary character. Transientsignals are characterized by an increase in power within the shortestperiods of time, often associated with preceding signal pauses or silentpassages. Stationary signals have a more continuous power timeline.

Interference can most effectively be reduced in the frequency domain ifthe magnitude spectra of the useful signal and that of the interferingsignal differ significantly.

Unfortunately this does not apply to transient useful signals (such asguiro and castanets) because they have an almost white spectrum andthere is little difference to the noise as interfering signal. Areduction in selective frequencies can hardly take place. The residualnoise is therefore high in such cases. Further disturbances are added:The processing of noise in the frequency domain and transformation backinto the time domain causes an alias, spread out over the block. It ismostly hidden for stationary useful signals.

As long as the transient useful signal is present, residual noise ismasked simultaneously. Residual noise that occurs after a transient canbe better masked, because the natural transient signals settle moreslowly, and hearing has temporal post-masking. The masking of residualnoise, which precedes a transient, is lower. In signal pauses before atransient noise, a so-called pre-echo can be audible.

FIG. 19 shows the masking in the time domain (“temporal masking”).

If the useful signal has a transient/impulse character and noise issuperimposed on the difference signal, then the residual noise can bereduced (the pre-echo amongst others), by an additional signalprocessing in the time domain (temporal processing). The differencesignal is herewith limited to the envelope of the sum signal (clipping).

The following images using an example of a transient signal show how atemporal processing reduces pre-echoes.

FIG. 20 shows an undisturbed guiro without signal processing, i.e., theoriginal signal.

FIG. 21 shows a noisy guiro after signal processing in the frequencydomain. A pre-echo is present.

FIG. 22 shows the noisy guiro after signal processing in the time andfrequency domain. The pre-echo is significantly reduced.

If the useful signal is transient and/or short signal pauses are presentwithin the block, then clipping can also help to temporally eliminate orreduce disturbances with a transient character.

The limiting to the envelope curve reduces the interfering energy in thecase of strong disturbances. In these cases, the magnitude spectrum ofthe difference signal after clipping lies below that of the untreatedmagnitude spectrum. The effect of the original disturbance on themagnitude and phase of spectral lines is reduced.

On the other hand, the clipping itself produces noise with a whitespectrum, which manifests itself as interferent portions in themagnitude and the phase of the difference signal spectrum. This effectincreases the more signal components are cut off. If it comes to a levelincrease in spectral lines in this regard, this can be corrected by thesignal processing in the frequency domain. Level reductions cannot becorrected.

The distorted phase spectrum is taken on unchanged.

It is therefore necessary to decide from block to block whether thelimiting to the envelope curve is to be applied.

8. Criterion for the Use of Temporal Processing

If the sum signal (useful signal) is stationary, or if it has atemporally continuous signal form, its frequency spectrum usuallyprovides sufficient gaps for an effective selective interferencereduction in the frequency domain of the difference signal. In the caseof stationary signals, the temporal processing (limiting to the envelopecurve) worsens the residual noise and thus also the channel separation.Therefore it is better to turn off temporal processing in this case.

In contrast, if the transients dominate or signal pauses exist withinthe signal, it is advantageous to additionally use temporal processing.In these instances, the temporal processing reduces the pre-echoes, inparticular. Pre-echoes occur as a form of alias after the IFFT, aredistinguishable in the signal pause before a transient, and may beaudible without temporal processing. In the case of stationary signals,the alias after the IFFT is usually masked by the continuous signalform.

From this follows Rule 3:

Rule 3: Temporal processing (limiting to the envelope curve) is turnedon, if in the sum signal (useful signal) transients dominate or whenthere are pauses within the signal.

It is useful to already check for the condition within the time domain,since a limiting to the envelope curve is, before the signal processing,in the frequency domain.

For identification of transients, the envelope of the sum signal σ isexamined. A transient is considered identified if the envelope curveincreases by more than x percent within a time segment Δt. Determinationin percentages allows for level-independent identification.

9. Signal Processing 9.1. Signal Processing in the Time Domain, Part 1(the Sequence of Steps 1 and 2 is Interchangeable).

-   1. Block forming of the audio sample values for the right and left    channel. An overlapping block structure is produced. The overlap is,    e.g., 50%. The block length is, e.g., 4096. The following processing    steps apply per block.-   2. Matrixing the channels L and R into

σ=(L+R)/2 and δ=(L−R)/2

-   -   (alternatively direct processing of the sum signal σ and        difference signal δ)

-   3. Signal analysis and limiting to the envelope

-   3.1 Identification of LS or IS on the basis of σ and δ    -   3.1.1 Temporal derivative of σ and δ Blocks do and dδ are        created    -   3.1.2 Calculation of the 1-normalized absolute value of the        covariance of do and dδ:        -   absKOVnorm    -   3.1.3 Calculation of the absolute value of the autocovariance of        dσ: absAKOV    -   3.1.4 Calculation of the difference

deltaKOV=absKOVnorm−absAKOV

-   -   3.1.5 Temporal limitation of deltaKOV to an upper limit (here, 3        ms):        -   deltaKOVlim is generated    -   3.1.6 Calculation of the maximum of deltaKOVlim    -   3.1.7 Identification of LS or IS:        -   Verification of SNR:        -   if rootSNR<rootSNR_(thresh) (or if SNR<SNRthresh {e.g.            0.3}):            -   the LS/IS-decision of the previous block is adopted                else:            -   if max (deltaKOV)<kovlevel (e.g. kovlevel<0.1):                -   IS            -   else: LS    -   3.1.8 Calculation of the envelope of σ regarding the values of        the time shift τ and of the amplitude factor Ampf, e.g.:

LS:τ _(LS)=+/−3.0 ms k _(LS)=1.4

IS:τ _(IS)=+/−3.0 ms k _(IS)=1.4

-   -   -   3.1.9 Identification of transients and limiting of δ:            -   Calculation of the percentage increase (PA) of the                envelope of σ within a time interval of n samples.            -   if PA<x %: stationary signal            -   else: detected transient, limiting the signal δ to the                envelope of σ        -   3.2 Weighting of each block with an analysis window function            (here, root-Hanning):            -   The weighted blocks wσ and wδ are created.

    -   9.2 Signal Processing in the Frequency Domain

-   4. Zero-padding ** of the weighted blocks wσ and wδ.

-   5. Transformation into the frequency domain. Outcome is the spectra    WΣ(f) and WΔ(f).

-   6. Separation into magnitude and phase spectra.

-   7. Calculation of the spectral correction function K(f) (see annex).

-   8. Multiplication of the magnitude spectrum of WΔ(f) by correcting    function K(f) in the linear measure.

-   9. Calculation of the corrected complex spectrum of WΔ(f).

-   10. Inverse transformation into the time domain. Outcome is a    corrected difference signal δ(t).    -   Padding the block with zeros to the desired length (power of 2        for FFT)    -   9.3 Signal Processing in the Time Domain, part 2

-   11. Multiplication of the block with a synthesis window function    (here, root-Hanning).

-   12. Overlap add of blocks

-   13. Dematrixing of σ and the corrected δ into the channels L and R

Annex A/Formulas: Hanning Window (Analysis and Synthesis WindowFunction)

H(n,N)=0.5−0.5 cos {(2Πn/(N−1)} where N=number of samples per block

root Hanning=√H(n,N)

Signal to Noise Ratio SNR within a Block:

SNR=P _(wσ) /P _(wδ) with P=power=rootSNR=√SNR

Covariance KOV and Autocovariance AKOV:

${{Mean}\mspace{14mu} {value}\mspace{14mu} {m(x)}}:={\frac{1}{n} \cdot {\sum\limits_{i = 0}^{n}x_{i}}}$${{Variance}\mspace{14mu} {{var}(x)}}:={\sum\limits_{i = 0}^{i_{\max}}\frac{\left( {x - {m(x)}} \right)^{2}}{i_{\max} - 1}}$${{Standard}\mspace{14mu} {deviation}\mspace{14mu} {{stdev}(x)}}:=\sqrt{{var}(x)}$${{Covariance}\mspace{14mu} {{kov}\left( {\sigma,\delta} \right)}_{i}}:={\sum\limits_{k}\left\lbrack {{{\left( {\sigma_{k} - {m(\sigma)}} \right) \cdot \left( {\delta_{i + k} - {m(\delta)}} \right\rbrack}{Normalized}\mspace{14mu} {covariance}\mspace{14mu} {{KOV}\left( {\sigma,\delta} \right)}_{i}}:={{\frac{{{kov}\left( {\sigma,\delta} \right)}_{i}}{i_{\max} \cdot {{stdev}(\sigma)} \cdot {{stdev}(\delta)}}{Autocovariance}\mspace{14mu} {{AKOV}(x)}_{i}}:={{KOV}\left( {x,x} \right)}_{i}}} \right.}$

Spectral Correction Function K (f) Considering the Spectra on a LinearScale:

-   -   local level maxima in the difference signal spectrum:    -   For LS:        -   Calculating the median filtered sum signal spectrum            WΣ(f)_(median) and difference signal spectrum WΔ(f)_(median)        -   Determining the frequencies f_(LM Diff) with local level            maxima (>LM_(Diff) dB) in WΔ(f)        -   Determining the frequencies f_(LM sum) with local level            maxima (>LM_(sum) dB) in WΣ(f)        -   if in a contiguous range of f_(LM Diff), a frequency            f_(LM sum) occurs, then

K(f)=1

-   -   -   otherwise:

if |WΔ(f)|>|WΣ(f)|:K(f)=|WΣ(f)|/|WΔ(f)|

if |WΔ(f)I≦|WΣ(f)|:K(f)=1

-   -   for IS:

if |WΔ(f)|>|WΣ(f)|:K(f)=|WΣ(f)/|WΔ(f)|

if |WΔ(F)|≦|WΣ(f)|:K(f)=1

Cancellations in the Sum Signal Spectrum:

-   -   For LS:        -   Calculating the median filtered sum signal spectrum            WΣ(f)_(median)        -   Identifying the frequencies f_(AL), for which            time-delay-dependent cancellations (narrow dips) take place            in WΣ(f).        -   if f=f_(AL) K(f)=WΣ(f)_(median)        -   else f:

if |WΔ(f)|>|WΣ(f)|:K(f)=WΣ(f)|/|WΔ(f)|

if |WΔ(f)|≦|WΣ(f)|:K(f)=1

-   -   For IS:

if |WΔ(f)|>|WΣ(f)|:K(f)=|WΣ(f)/|WΔ(f)|

if |WΔ(f)|≦|WΣ(f)|:K(f)=1

The method according to the invention reduces noise and other types ofinterference that occur in the difference signal and disturbances thatexceed the sum signal. Interferences include those caused by thetransmission chain after matrixing in the stereo coder up to the FMdemodulator in the receiver, e.g., inherent noise of the FM transmitter;radio transmission interference; noise due to low power of the receivingantenna; the inherent noise in the RF part of the receiver; RF-adjacentchannel and co-channel interference; quantization noise of the ADCs inthe IF-range of the receiver; non-linear distortion products due to thelimitation of the IF bandwidth (as long as they are not within the sumchannel); disturbances due to signals of purely digital or hybridtransmission systems, such as IBOC, HD Radio and FMeXtra; anddisturbances and crosstalk within hybrid systems, which have an impacton the difference signal of the analog transmission system.

Interference that occurs in the sum channel, i.e., also in the case ofpure mono-reception, cannot be eliminated by this method. This includesadjacent channel interference, which can particularly cause brief butstrong disturbances during mobile reception.

The improvements mentioned also refer to the applied FM variant SSBSC inthe USA. The invention approach is fully compatible with SSBSC.

The method was simulated and emulated in this exemplary embodiment witha mathematical program on a PC.

Referring to the block diagrams according to FIGS. 23a to 25, anexemplary embodiment of the method according to the invention is to beexplained.

As shown in FIG. 23a , the analog FM stereo signal is first digitizedand matrixed. For a receiver with digital signal processing, thealready-digitized signal can be used.

The signal is divided into a sum signal and a difference signal in thetime domain, and weighted, overlapping blocks are generated. Theweighting can, for example, be carried out using the Hanning function(window function).

The sum signal is used both for the calculation of the envelope curveand for the identification of time-based stereophony (LS) and intensitystereophony (IS).

The identification of LS and IS preferably takes place, as previouslydescribed, by means of a correlation analysis.

The difference signal can be lowered to the envelope curve of the sumsignal.

For this purpose, according to a preferred embodiment of the invention,a transient detection is provided, which decides whether it is atransient or stationary signal. In the case of a stationary signal, alimiting to the envelope is not performed and the unchanged differencesignal is used immediately.

The transient signal, on the other hand, is subjected to the limitationto the envelope curve of the sum signal.

Then, both the sum signal and the difference signal are transformed fromthe time domain into the frequency domain.

The frequency range, or the part of the method in which the processingtakes place in the frequency domain, is marked in this block circuitdiagram in the dotted frame, which is characterized by frequency range.

There is now a sum signal spectrum which has an amount as well as adifference signal spectrum, which also has an amount.

The phase of the difference signal spectrum is processed furtherunchanged.

As shown in FIG. 23b , cancellations at certain frequencies areidentified over the sum signal spectrum.

The affected frequencies or spectral lines can be defined by means of anidentification and comparison of the maxima of the sum signal spectrumand the difference signal spectrum.

At cancellations, the difference signal spectrum is reduced to themedian value of the sum signal spectrum.

The identification of cancellations is explained below with reference toFIG. 24.

Identification and comparison of the maxima is explained below withreference to FIG. 25.

In the case of intensity stereophony, the difference signal spectrum isdirectly processed further without the need for identifyingcancellations and local maxima, or the need to use the identificationprocess in this exemplary embodiment.

For all frequencies that are not identified, rule 1 is executed in thefrequency domain and the difference signal spectrum is reduced to thesum signal spectrum.

A corrected difference signal spectrum is generated. This is transformedback into the time domain using the phase spectrum.

After weighting and combining the overlapping blocks in the time domain,a corrected difference signal is generated.

The sum signal and the corrected difference signal are dematrixed and acorrected stereo signal is generated.

FIG. 24 shows an embodiment of the identification of cancellations shownas a block in FIG. 23 b.

The logarithmized sum signal spectrum is compared with its median curve.If the difference is above a threshold value, the difference signalspectrum is reduced to the respective median value. If not, rule 1applies and the difference signal spectrum is reduced to the sum signalspectrum as shown in FIG. 23 b.

FIG. 25 shows the identification of the maxima depicted in FIG. 23 b.

Both the logarithmized sum signal spectrum and the logarithmizeddifference signal spectrum are subjected to a median filtering.

If the respective difference is above a threshold value, a maximum canbe identified.

If a maximum of the sum signal spectrum is within the frequencybandwidth of the maximum of the difference signal spectrum, thedifference signal spectrum is not lowered for this frequency bandwidth.

By means of the invention, a reduction of disturbances of a stereosignal can take place, so that this reaches approximately the quality ofthe monosignal.

What is claimed is:
 1. A method for processing an FM stereo signal,comprising the following steps: digitizing the analog FM stereo signalas a sum and difference signal; dividing the digitized signal intooverlapping blocks; transforming the overlapping blocks into a frequencydomain; comparing spectral lines of a difference signal spectrum withspectral lines of a sum signal spectrum; lowering at least the spectrallines of the difference signal spectrum, if these, in each case, have ahigher magnitude than a respective spectral line of the sum signalspectrum; transforming back the sum and difference signal spectrum andmerging the overlapping blocks.
 2. The method for processing the FMstereo signal according to claim 1, characterized in that, if the widthof a relative minimum of the spectrum of the sum signal is below athreshold value and the depth exceeds a threshold value and there isthus a cancellation, the spectral lines of the difference signal are notlowered or less lowered.
 3. The method for processing the FM stereosignal according to claim 1, characterized in that, in a range of alocal maximum of the difference signal spectrum, the difference signalspectrum is compared with the sum signal spectrum and the differencesignal spectrum is not lowered in this range if a maximum of the sumchannel spectrum lies within the frequency bandwidth of the maximum ofthe difference signal spectrum.
 4. The method for processing the FMstereo signal according to claim 2, characterized in that differences inthe time between sum and difference signals or between parts of bothsignals are determined by means of a similarity analysis or by means ofa correlation in the time domain or frequency domain, and that the stepsaccording to claim 2 are carried out in case of differences in time. 5.The method for processing the FM stereo signal according to claim 2,characterized in that, in case of a cancellation of a spectral line ofthe sum signal spectrum, the spectral line of the difference signalspectrum is only lowered to a spectral substitute value of the sumsignal spectrum.
 6. The method for processing the FM stereo signalaccording to claim 1, characterized in that the difference signal in thetime domain is limited to an envelope curve of the sum signal whosemaxima/minima are held (peak hold) for a period of time before and afterthe peak entry time, and the thus-changed envelope curve of the sumsignal is multiplied by a factor greater than
 1. 7. The method forprocessing the FM stereo signal according to claim 6, characterized inthat the limitation of the difference signal in the time domain to theenvelope curve of the sum signal is only performed when a transientcharacter of the signal is detected via an evaluation of the sum signalor its envelope curve.
 8. The method for processing the FM stereo signalaccording to claim 1, wherein the digital signal processing is performedsuch that the FM stereo signal is viewed so that its signal portions canonly be located within the stereo base.
 9. A computer program comprisinga plurality of instructions which can be stored on a computer, whenprocessed by a microprocessor or microcontroller, performing the methodaccording to claim
 1. 10. A consumer electronics device or smartphone,comprising means for carrying out the method according to claim
 1. 11.The consumer electronics device or smartphone according to claim 10,wherein the means for carrying out the method comprise anapplication-specific integrated circuit (ASIC) or a logical circuitprogrammed according to claim
 1. 12. The method for processing an FMstereo signal according to claim 1, wherein the spectral lines of thedifference signal spectrum are lowered to the magnitude of therespective spectral line of the sum signal spectrum.
 13. The method forprocessing an FM stereo signal according to claim 3, characterized inthat differences in the time between sum and difference signals orbetween parts of both signals are determined by means of a similarityanalysis or by means of a correlation in the time domain or frequencydomain, and that the steps according to claim 3 are carried out in caseof differences in time.
 14. The method for processing an FM stereosignal according to claim 5, characterized in that the spectral line ofthe difference signal spectrum is lowered to a median value of the sumsignal spectrum.